🎮 The Next Input — Issue #201

In partnership with

⚡ The Briefing — 60 sec

• Sam Altman is ready to decelerate “But don’t pump the brakes on my cash flow though.” After years of “faster, faster, faster,” OpenAI is now suggesting the world might need time to catch up. Fair point. Convenient timing.

• Trump administration bans new Chinese humanoid robots Another day, another Trump ban. This time it’s Chinese humanoid robots, quadrupeds and connected power equipment. The AI race is no longer merely about who builds the best technology—it’s increasingly about whose technology governments will allow through the door.

• Apple becomes the second-ever $5tn company as investors flee AI stocks Did you say $5tn? While investors reconsider whether every AI infrastructure cheque needs another zero, Apple has somehow turned being late to the arms race into a safe-haven strategy. Remarkable scenes.

🛠️ The Playbook — AI Exposure Stress Test

Mission
Identify where your AI strategy could break if vendors slow down, markets reprice, governments intervene or critical technology becomes unavailable.

Difficulty
Intermediate

Build time
3–5 hours

ROI
Reduces strategic dependency and keeps essential workflows operating when the AI market inevitably gets weird.

0) Why This Matters

AI strategy is often built on several assumptions:

• models will keep improving quickly

• compute will remain available

• vendors will remain friendly

• pricing will remain tolerable

• governments will permit access

• investors will keep funding the infrastructure

None of those assumptions is guaranteed.

A frontier lab can slow development. A regulator can restrict a product. A government can block foreign hardware. A market correction can force suppliers to change pricing, roadmaps or priorities.

Resilience starts by asking an uncomfortable question:

What stops working if the AI environment changes tomorrow?

1) Architecture

2) Workflow

1. List every business-critical workflow currently using AI.

2. Record the model, vendor, region, infrastructure and data source supporting each workflow.

3. Score each dependency by operational importance, replaceability and switching time.

4. Simulate vendor failure, price increases, model degradation, regulatory bans and compute shortages.

5. Define fallback providers, manual procedures and approval owners for critical workflows.

6. Test the contingency plan quarterly and update it whenever vendors or regulations change.

3) Example Prompts

Dependency Audit

You are an AI operational resilience analyst.

Review the supplied AI workflows and identify:

- single-vendor dependencies
- model-specific dependencies
- geographic or jurisdictional exposure
- unavailable fallback processes
- proprietary features that are difficult to replace
- workflows that would stop immediately during an outage

Return:
1. dependency register
2. risk rating
3. expected operational impact
4. estimated switching difficulty
5. recommended mitigation

Disruption Scenario

Stress-test this AI system against the following scenarios:

- primary model unavailable for seven days
- API pricing increases by 300%
- government restricts access to the provider
- model quality declines after an update
- cloud region becomes unavailable
- sensitive data can no longer leave Australia

For each scenario, provide:
1. affected workflows
2. immediate impact
3. fallback process
4. accountable owner
5. recovery target
6. preventative control

Vendor Exit Plan

Create a vendor exit plan for the following AI platform:

[PLATFORM]

Include:
- data and prompt exports
- replacement-provider requirements
- model evaluation criteria
- workflow migration sequence
- security and identity changes
- testing requirements
- rollback procedure
- expected downtime
- stakeholder communications

Prioritise business continuity over feature parity.

4) Guardrails

• Do not label a workflow resilient merely because another model API exists.

• Test fallback quality using real organisational tasks.

• Keep business logic separate from individual model providers.

• Maintain exportable prompts, data schemas and workflow configurations.

• Document manual fallback procedures for critical services.

• Track jurisdiction and data-residency requirements.

• Review vendor contracts for suspension, termination and pricing-change rights.

• Assign named owners to every contingency action.

5) Pilot Rollout — 3 hours

1. Select one AI workflow the business cannot comfortably lose for a week.

2. Document every vendor, model, integration and dataset it relies on.

3. Score each dependency for impact, replaceability and recovery time.

4. Configure one alternative model or manual fallback path.

5. Run the workflow with the primary provider disabled.

6. Record quality loss, recovery time and missing controls before updating the plan.

6) Metrics

• Percentage of critical AI workflows documented

• Single-provider dependency rate

• Successful failover rate

• Mean time to switch providers

• Quality difference during failover

• Percentage of workflows with manual fallback

• Vendor concentration by business impact

• Unplanned AI downtime

• Cost increase tolerance

• Contingency-test completion rate

Pro Tip: Your AI strategy is not resilient because the vendor has a status page. It is resilient when their status page can turn red and your business keeps moving.

🎯 The Arsenal — Tools & Platforms

• Azure AI Foundry · evaluates and operates models across governed enterprise workflows · Link

• LangGraph · separates workflow logic from individual model providers · Link

• Airtable · maintains a practical vendor and dependency register · Link

• Microsoft Entra ID · manages identity and emergency access controls · Link

• Power BI · monitors AI cost, uptime, quality and concentration risk · Link

Copy-paste prompt block:

You are an enterprise AI resilience architect.

Assess the operational resilience of my AI stack.

Organisation:
[DESCRIPTION]

Critical AI workflows:
[LIST]

Models and vendors:
[LIST]

Cloud and data infrastructure:
[LIST]

Jurisdictions involved:
[LIST]

Current fallback processes:
[LIST]

The assessment must cover:
- vendor concentration
- model portability
- regulatory and geopolitical exposure
- data-residency constraints
- pricing risk
- provider outages
- model degradation
- manual fallback capability
- recovery ownership

Return:
1. dependency map
2. risk register
3. critical failure scenarios
4. fallback architecture
5. vendor exit plans
6. quarterly test schedule
7. executive summary
8. operational metrics

💡 Free Office Hours

The AI market will not move in a perfectly straight line. Providers will accelerate, decelerate, reprice and occasionally find themselves on the wrong side of government policy. A resilient architecture lets you benefit from the frontier without being held hostage by it.

Book here: https://calendly.com

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🕹️ Game Over

AI is moving too quickly, markets say it is moving too expensively, and governments say some of it is not moving across the border at all.

Plan accordingly.

— Aaron Automating the boring. Amplifying the brilliant.

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